My Initial import looks like this and this code block runs fine.
# Libraries to help with reading and manipulating data
import numpy as np
import pandas as pd
# Libraries to help with data visualization
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
# Removes the limit for the number of displayed columns
pd.set_option("display.max_columns", None)
# Sets the limit for the number of displayed rows
pd.set_option("display.max_rows", 200)
# to split the data into train and test
from sklearn.model_selection import train_test_split
# to build linear regression_model
from sklearn.linear_model import LinearRegression
# to check model performance
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
But when I try to following command I get the error ModuleNotFoundError: No module named 'sklearn.externals.joblib'
I tried to use !pip to install all the modules and other suggestions for this error it didnt work. This is google colab so not sure what I am missing
from mlxtend.feature_selection import SequentialFeatureSelector as SFS
For the second part you can do this to fix it, I copied the rest of your code as well, and added the bottom part.
# Libraries to help with reading and manipulating data
import numpy as np
import pandas as pd
# Libraries to help with data visualization
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
# Removes the limit for the number of displayed columns
pd.set_option("display.max_columns", None)
# Sets the limit for the number of displayed rows
pd.set_option("display.max_rows", 200)
# to split the data into train and test
from sklearn.model_selection import train_test_split
# to build linear regression_model
from sklearn.linear_model import LinearRegression
# to check model performance
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
# I changed this part
!pip install mlxtend
import joblib
import sys
sys.modules['sklearn.externals.joblib'] = joblib
from mlxtend.feature_selection import SequentialFeatureSelector as SFS
it works for me.